Optimal Allocation of Pauli Measurements for Low-Rank Quantum State Tomography: Balancing Measurement Settings and Repetitions
For low-rank quantum state tomography using Pauli measurements, maximizing the number of measurement settings (K) while minimizing repetitions per setting (M) - even to the extreme of single-sample measurements (M=1) - can be optimal for minimizing recovery error when the total number of state copies (KM) is fixed.
Efficient Learning of Mixed-State Tomography for Open Photonic Quantum Walk Using a Neural Density Operator and Generalized Natural Gradient Descent
This research demonstrates a novel, efficient method for reconstructing the full density matrix of an open quantum walk system using a neural network approach, achieving high fidelity with fewer measurements than traditional methods.
Quantum State Tomography of Photonic Qubits: Challenges and Efficiency in Realistic Conditions with Coherent Light Sources
This research paper investigates the efficiency of Quantum State Tomography (QST) for photonic qubits under realistic experimental conditions, focusing on the impact of noise sources like shot noise, attenuation, Raman scattering, and crosstalk, particularly in the context of wavelength-division multiplexing (WDM) systems.
Sample-Optimal and Memory-Efficient Quantum State Tomography with Discrete Measurements
This paper introduces a novel quantum state tomography algorithm that achieves both sample optimality and memory efficiency by leveraging unitary Schur sampling and a novel discretization of continuous Haar random measurements.
Quantum State Tomography for Mixed States Using Locally Purified Density Operators and Local Measurements
This paper introduces a novel quantum state tomography method, Grad-LPDO, which efficiently reconstructs mixed quantum states using locally purified density operators (LPDOs) and local measurements, demonstrating superior efficiency, accuracy, and robustness compared to previous methods.
Efficient Tomography Method for Large Cluster States of Microwave Photonic Qubits with Experimental Demonstration and Performance Analysis
This research paper presents a novel, efficient tomography method for characterizing large cluster states of entangled photonic qubits, demonstrating its effectiveness by reconstructing the density matrices of cluster states with up to 35 microwave photonic qubits and analyzing their entanglement properties.
1차원 구조화 양자 상태를 위한 샘플 최적 양자 상태 단층 촬영 및 이의 수렴 분석 증명 포함
본 논문에서는 1차원에서 MPO로 표현되는 구조화된 양자 상태에 대한 샘플 최적 양자 상태 단층 촬영 기법을 제시하고, 정보 이론적 한계에 도달하는 샘플 복잡도를 달성할 수 있음을 증명합니다. SIC-POVM 및 구형 t-디자인을 포함한 정보적으로 완전한 POVM을 사용하여 상태 복구 오류를 보장하는 데 필요한 상태 복사본의 수가 MPO의 독립 매개변수 수에 비례함을 보여줍니다. 또한, 제약된 최소 제곱 문제를 해결하기 위한 투영 경사 하강 알고리즘을 제안하고, 적절한 초기화를 통해 경험적 측정값에서 기반 상태를 효율적으로 복구할 수 있음을 보여줍니다.
Sample-Optimal Quantum State Tomography for Matrix Product Operator States Using Informationally Complete POVMs
This research paper presents a novel approach to efficiently reconstruct quantum states represented by Matrix Product Operators (MPOs) using informationally complete POVMs, achieving sample complexity proportional to the number of parameters in the MPO.
Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates
Quantum states prepared by Clifford gates and O(log n) non-Clifford gates can be efficiently learned using a polynomial number of copies and time.
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